Senior Associate, Data Scientist - Anti-Money Laundering

Capital One Financial

Quick summary

Work type
On-site
Location
McLean, VA · Richmond, VA · Chicago, IL · Plano, TX
Salary
$123,300–$140,700 / yr
Posted
39 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $171k
This role $132k
$112k most similar roles pay here $228k

This role pays less than 70% of similar roles. Most pay $126,800–$214,500 — the shaded band above. At the midpoint, this role pays about $132k versus about $171k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Senior Associate, Data Scientist - Anti-Money Laundering

As a Senior Associate Data Scientist on the Anti-Money Laundering Modeling and Advanced Data Insights team at Capital One, you will partner with data scientists, software engineers, risk managers, and product owners to develop predictive models and monitoring dashboards using AWS, Snowflake, Python, Spark, and other tools. Your day-to-day responsibilities include building machine learning models through all phases of development from design to implementation, ensuring they are production-ready for transaction monitoring and customer risk rating. You will need experience in AML modeling or related fields like fraud detection and credit risk management, along with proficiency in Python and SQL. This role requires innovative thinking, creativity, technical expertise, and a strong statistical background to address complex business problems at scale within the financial services industry.

What you'll do

  • Develop and deploy machine learning models to detect money laundering and fraud.
  • Build production-ready data pipelines using Python, AWS, Spark, and other tools.
  • Design, train, evaluate, validate, and implement predictive models for AML programs.
  • Collaborate with risk managers and product owners to enhance risk management products.
  • Source and preprocess data for model development and scoring in a production environment.

What we're looking for

  • At least 1 year of experience in AML modeling or related risk management domain.
  • Strong proficiency in Python and SQL for data analysis and model development.
  • Experience working with AWS for cloud-based solutions and services.
  • Ability to build machine learning models through all phases of the development lifecycle.
  • Collaborative skills to work effectively with cross-functional teams including data scientists, engineers, and business analysts.

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Senior Associate, Data Scientist - Financial Services

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